The background description provided herein is for the purpose of generally presenting the context of the disclosure. Unless otherwise indicated herein, the materials described in this section are not prior art to the claims in this application and are not admitted to be prior art by inclusion in this section.
The promise of smart environments (e.g., the “smart home”) and the Internet of Things (IoT) relies on robust sensing of diverse environmental facets. Traditional approaches rely on measuring one particular aspect of an environment with special-purpose sensors. Regardless of the approach taken, the goal remains the same: to apply sensing and computation to enhance the human experience, especially as it pertains to physical contexts (e.g., home, office, workshop) and the amenities contained within. Numerous approaches have been attempted and articulated, though none have reached widespread use to date.
One option is for users to upgrade their environments with newly released “smart” devices (e.g., light switches, kitchen appliances), many of which contain sensing functionality. However, this sensing is generally limited to the appliance itself (e.g., a smart light sensing whether it is on or off) or single parameter associated with its core function (e.g., a smart thermostat sensing whether the room is occupied). Likewise, few smart devices are interoperable, forming silos of sensed data that thwart a holistic experience. Instead of achieving a smart home, the best one can currently hope for are small islands of smartness. This approach also carries a significant upgrade cost, which so far has proven unpopular with consumers, who generally upgrade appliances in a piecemeal manner.
A variety of different sensing modalities have been described in the context of environmental sensing, including special-purpose sensing systems, distributed sensing systems, infrastructure-mediated sensing systems, and general-purpose sensing systems. These sensing modalities can be organized according to the number of sensors that they utilize and the number of facets or parameters that they sense. In particular, special-purpose sensing systems utilize a single sensor, infrastructure-mediated and general-purpose sensing systems utilize one or a few sensors, and distributed sensing systems utilize many sensors. Further, special-purpose sensing systems sense a single facet, infrastructure-mediated sensing systems tend to sense one or a few facets, general-purpose sensing systems tend to sense many facets, and distributed sensing systems can sense anywhere from a single facet to many facets of an environment.
However, currently existing sensing systems typically transfer all the sensed data to a backend server for processing and/or storage system leading to problems relating to, for example, bandwidth usage and processing speed.